mydataset.ipynb
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Kernel status: Idle
[18]:
pwd
[18]:
'C:\\Users\\l'
import pandas as pd
[38]:
df = pd.read_csv('mydataset.csv')
[40]:
print(df.head())
Rank Name Platform Year Genre Publisher \ 0 1 Wii Sports Wii 2006.0 Sports Nintendo 1 2 Super Mario Bros. NES 1985.0 Platform Nintendo 2 3 Mario Kart Wii Wii 2008.0 Racing Nintendo 3 4 Wii Sports Resort Wii 2009.0 Sports Nintendo 4 5 Pokemon Red/Pokemon Blue GB 1996.0 Role-Playing Nintendo NA_Sales EU_Sales JP_Sales Other_Sales Global_Sales 0 41.49 29.02 3.77 8.46 82.74 1 29.08 3.58 6.81 0.77 40.24 2 15.85 12.88 3.79 3.31 35.82 3 15.75 11.01 3.28 2.96 33.00 4 11.27 8.89 10.22 1.00 31.37
[42]:
shape = df.shape
[44]:
print(f"The shape of the DataFrame is: {shape}")
The shape of the DataFrame is: (16598, 11)
[46]:
headers = df.columns
[48]:
print("Headers of the dataset:")
print(headers.tolist())
Headers of the dataset: ['Rank', 'Name', 'Platform', 'Year', 'Genre', 'Publisher', 'NA_Sales', 'EU_Sales', 'JP_Sales', 'Other_Sales', 'Global_Sales']
[50]:
print(headers.tolist())
['Rank', 'Name', 'Platform', 'Year', 'Genre', 'Publisher', 'NA_Sales', 'EU_Sales', 'JP_Sales', 'Other_Sales', 'Global_Sales']
First 5 rows of the dataset:
Rank Name Platform Year Genre Publisher \
0 1 Wii Sports Wii 2006.0 Sports Nintendo
1 2 Super Mario Bros. NES 1985.0 Platform Nintendo
2 3 Mario Kart Wii Wii 2008.0 Racing Nintendo
3 4 Wii Sports Resort Wii 2009.0 Sports Nintendo
4 5 Pokemon Red/Pokemon Blue GB 1996.0 Role-Playing Nintendo
NA_Sales EU_Sales JP_Sales Other_Sales Global_Sales
0 41.49 29.02 3.77 8.46 82.74
1 29.08 3.58 6.81 0.77 40.24
2 15.85 12.88 3.79 3.31 35.82
3 15.75 11.01 3.28 2.96 33.00
4 11.27 8.89 10.22 1.00 31.37
Last 5 rows of the dataset:
Rank Name Platform \
16593 16596 Woody Woodpecker in Crazy Castle 5 GBA
16594 16597 Men in Black II: Alien Escape GC
16595 16598 SCORE International Baja 1000: The Official Game PS2
16596 16599 Know How 2 DS
16597 16600 Spirits & Spells GBA
Year Genre Publisher NA_Sales EU_Sales JP_Sales \
16593 2002.0 Platform Kemco 0.01 0.00 0.0
16594 2003.0 Shooter Infogrames 0.01 0.00 0.0
16595 2008.0 Racing Activision 0.00 0.00 0.0
16596 2010.0 Puzzle 7G//AMES 0.00 0.01 0.0
16597 2003.0 Platform Wanadoo 0.01 0.00 0.0
Other_Sales Global_Sales
16593 0.0 0.01
16594 0.0 0.01
16595 0.0 0.01
16596 0.0 0.01
16597 0.0 0.01
Statistical summary of the dataset:
Rank Year NA_Sales EU_Sales JP_Sales \
count 16598.000000 16327.000000 16598.000000 16598.000000 16598.000000
mean 8300.605254 2006.406443 0.264667 0.146652 0.077782
std 4791.853933 5.828981 0.816683 0.505351 0.309291
min 1.000000 1980.000000 0.000000 0.000000 0.000000
25% 4151.250000 2003.000000 0.000000 0.000000 0.000000
50% 8300.500000 2007.000000 0.080000 0.020000 0.000000
75% 12449.750000 2010.000000 0.240000 0.110000 0.040000
max 16600.000000 2020.000000 41.490000 29.020000 10.220000
Other_Sales Global_Sales
count 16598.000000 16598.000000
mean 0.048063 0.537441
std 0.188588 1.555028
min 0.000000 0.010000
25% 0.000000 0.060000
50% 0.010000 0.170000
75% 0.040000 0.470000
max 10.570000 82.740000
Data types of each attribute in the dataset: Rank int64 Name object Platform object Year float64 Genre object Publisher object NA_Sales float64 EU_Sales float64 JP_Sales float64 Other_Sales float64 Global_Sales float64 dtype: object
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